Estimating the true (population) infection rate for COVID-19: A Backcasting Approach with Monte Carlo Methods

Steven J. Phipps, R. Quentin Grafton, Tom Kompas

Type: Dataset

Publication Date: 2020-05-12

Citations: 0

DOI: https://doi.org/10.5281/zenodo.3821525

View Publication

Locations

Zenodo (CERN European Organization for Nuclear Research) - View
DataCite API - View

Similar Works

Action	Title	Year	Authors
+ PDF Chat	Estimating the true (population) infection rate for COVID-19: A Backcasting Approach with Monte Carlo Methods	2020	Steven J. Phipps R. Quentin Grafton Tom Kompas
+	Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach	2020	Steven J. Phipps R. Quentin Grafton Tom Kompas
+	Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach	2020	Steven J. Phipps R. Quentin Grafton Tom Kompas
+	Robust estimates of the true (population) infection rate for COVID-19: a backcasting approach	2020	Steven J. Phipps R. Quentin Grafton Tom Kompas
+	Robust estimates of the true (population) infection rate for COVID-19: A backcasting approach: Estimates of infection rate for COVID-19	2020	Steven J. Phipps R. Quentin Grafton Tom Kompas
+	Estimating population infection rates from non-random testing data: Evidence from the COVID-19 pandemic	2024	David Benatia Raphaël Godefroy Joshua Lewis
+	First back-calculation and infection fatality multiplier estimate of the hidden prevalence of COVID-19 in Ireland	2021	Catherine Comiskey Anne Snel Prakashini Banka
+	A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors	2021	Lucas Böttcher Maria R. D’Orsogna Tom Chou
+	A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors	2021	Lucas Böttcher Maria R. D’Orsogna Tom Chou
+	A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors	2021	Lucas Böttcher Maria R. D’Orsogna Tom Chou
+	Estimation of testing bias in covid-19	2020	Díaz-Pachón Da Rao Js
+ PDF Chat	Inferring True COVID19 Infection Rates From Deaths	2020	Ian McCulloh Kevin S. Kiernan Trevor Kent
+ PDF Chat	A Method for Estimating the Number of Infections From the Reported Number of Deaths	2021	Åke Brännström Henrik Sjödin Joacim Rocklöv
+ PDF Chat	Assessing the Spread of the Novel Coronavirus in the Absence of Mass Testing	2020	David Miles Oscar Dimdore‐Miles
+ PDF Chat	A simple correction for COVID-19 sampling bias	2020	Daniel Andrés Díaz–Pachón J. Sunil Rao
+	Covid-19 prevalence estimation by random sampling in the wider population - Optimal sample pooling under varying assumptions about true prevalence	2020	Ola Brynildsrud
+	Inferring the number of COVID-19 cases from recently reported deaths [version 1;peer review: awaiting peer review]	2020	Thibaut Jombart Christopher I Jarvis Nikos I Bosse Adam J. Kucharski W. John Edmunds
+ PDF Chat	Inferring community transmission of SARS-CoV-2 in the United Kingdom using the ONS COVID-19 Infection Survey	2023	Ruth McCabe Gabriel Danelian Jasmina Panovska‐Griffiths Christl A. Donnelly
+	Peer Review #3 of "Confidence in the dynamic spread of epidemics under biased sampling conditions (v0.1)"	2020	F Liu
+	Peer Review #1 of "Confidence in the dynamic spread of epidemics under biased sampling conditions (v0.1)"	2020	Mutasem K. Alsmadi

Works That Cite This (0)

Action	Title	Year	Authors

Works Cited by This (0)

Action	Title	Year	Authors